Staging and therapy of cutaneous melanoma patients with sentinel lymph node biopsies and the use of systemic adjuvant therapy in those with high risk primary lesions and/or regional lymph node metastases lately have become commonplace, although neither intervention has been shown unequivocally to improve overall survival. These, together with the promulgation of the recent extensive revision of the AJCC staging system, make it particularly timely and important to develop further, validate and export prognostic models that will be used for designing efficient clinical trials and for clinical management of patients with melanoma. The overall objective of this project remains to impact positively on melanoma's management and mortality by developing and testing prognostic models using a well documented and carefully followed cohort of approximately 5,000 melanoma patients assembled since 1972 and an archive of tissue blocks of primary lesions for a representative sample these patients. In specific aim 1 we will establish both better modeling techniques and more robust prognostic factors by the application of innovative biostatistical methods to address the candidacy of clinical and new immunohistologic biomarkers. Specific aims 2 and 3 are designed to continue development of models whose use will I) protect patients with "minimal risk" melanomas from the morbidity and cost of excessive investigation and therapy, and 2) better calibrate investigation and management of patients with metastatic capacity by clinical trialists and clinicians by predicting the likelihood of a SLN biopsy revealing melanoma and of metastasis-free survival with and without regional surgical staging and therapy. To optimize surveillance and allow early intervention for additional primary melanomas in follow-up, in specific aim 4 we will develop prognostic models for predicting the occurrence of a second primary melanoma. These new models will ultimately incorporate information on patients' MC1R and CDKN2A genotypes. To promote the use of models by trialists and practitioners, in all models we will develop individualized patient probabilities for the occurrence of clinically relevant events and will accomplish external validation with intra- and extra-SPORE collaborators.